Token Identifiability: Protocols & Challenges

• Token identifiability is the capacity to securely and provably link a digital token to its underlying referent using cryptographic, protocol, and ledger-based mechanisms.
• Empirical analyses reveal that many tokens suffer from weak decentralized metadata, with only about 40% featuring robust, tamper-resistant storage, affecting trust.
• Layered token composition and cryptographic controls enable traceable provenance and selective privacy, essential for KYC/AML compliance and digital identity applications.

Token identifiability refers to the capacity to reliably, authentically, and provably link a digital token—whether for assets, payment instruments, or attestations—to its underlying referent (an object, person, digital artifact, or credential). In digital systems, identifiability is a condition for durable value, trust, traceability, and often regulatory compliance. Its realization relies on cryptographic, protocol, and ledgertopological mechanisms. However, practical deployments often fall short due to weak asset binding, susceptibility to mutability or duplication, and ecosystem fragmentation.

1. Core Properties Governing Token Identifiability

Three properties—permanence, immutability, and uniqueness—are foundational for NFT identifiability, as established in the analysis of ERC-721 metadata (Barrington et al., 2022). Their definitions are operational:

• Permanence: The token and its referenced metadata/content must exist in a persistent, publicly verifiable location, ideally decentralized (on-chain or IPFS).
• Immutability: The on-chain contract is immutable, but this is insufficient unless the referred asset and metadata are also stored in immutable, content-addressable media.
• Uniqueness: A token must correspond to a unique digital artifact; non-fungibility at the ledger level is not sufficient if tokens reference the same or mutable metadata.

Empirical paper of 7,020,950 ERC-721 tokens showed only 40.18% have metadata in decentralized, tamper-resistant storage, with 45.07% in mutable, centralized forms, and 14.75% unreadable (Barrington et al., 2022). Immutability, by misdesign or operational error, is often violated unless stringent asset storage procedures are followed. Absence of content hashing is a frequent source of broken asset uniqueness.

Storage Type	% of Tokens
Permanent (decentralized)	40.18%
Non-permanent (centralized)	45.07%
Not readable	14.75%

A plausible implication is that, even when "non-fungible," nearly half of tokens lack reliable identifiability, leading to trust and valuation failures in marketplaces.

2. Identifiability through Token Composition and Topological Traceability

Tokens may be constructed in layered, compositional fashion—e.g., wrapped tokens, liquidity pool shares, vault receipts. The token composition graph defines identifiability in terms of directed dependencies: an edge from $\mathcal{X}$ to $\mathcal{Y}$ if $\mathcal{X}$ can be deposited to mint $\mathcal{Y}$, with redemption symmetry (Harrigan et al., 3 Nov 2024).

The graph, constructed via EVM logs and tokenising meta-events (deposit+mint, withdraw+burn), allows tracing through compositional dependencies:

• Vertices: Unique token contracts.
• Edges: Proven bi-directional tokenising events.

Absence of cycles, presence of long directed paths (up to 9 layers deep), and large connected components encode transitive provenance and identifiability. Compositional structure is central for synthetic asset tracing, liquidity pools, and stablecoin collateralization.

A plausible implication is that tokens with high in-degree/out-degree (in this graph) tend to be better collateralized and more readily have their underlying assets auditable, enhancing identifiability. Tokens isolated from the composition graph display lower identifiability and market activity.

3. Identifiability in Payment and Asset Tracking Systems

Digital payment systems manifest two principal identifiability paradigms (Goodell, 2022):

• Endogenous Tracking: The ledger directly records asset creation/spend (e.g., Bitcoin UTXO), supporting fine-grained traceability but at the expense of privacy.
• Oblivious Tracking: Assets carry own provenance chains (e.g., TODA, Chaumian assets), with the ledger storing only hash commitments, reducing traceability and identifiability unless asset-level histories are public.

Privacy-enhancing technologies (blind signatures, zero-knowledge proofs) lower identifiability by severing dataset links, but compromise audit trails and accountability. Distributed ledger technology (DLT) can either enable strong identifiability by enforcing public record transparency or reduce it if only hashed commitments are posted.

Formally, in UTXO systems:

$$\text{Ledger stores: } \{ (\text{token}_i, \text{creation}, \text{spending}) \}$$

and identifiability is proportional to ledger visibility. In oblivious systems:

$$\text{token identifiability} \propto \text{provenance transparency}$$

A plausible implication is that payment system design is a fundamental determinant of identifiability/fungibility/privacy.

4. Cryptographic and Protocol Mechanisms for Identifiability Control

Cryptographic primitives enforce or restrict identifiability:

• Blind signatures and zero-knowledge proofs sever the linkage between issuance and utilization, as in DigiCash or Monero.
• Threshold encryption, as implemented in IdentityChain (Darabi et al., 14 Jul 2024), enables selective identity disclosure only upon multi-party committee consent, ensuring default privacy with regulated accountability.

IdentityChain applies pseudorandom functions for anonymous account IDs:

$RegID_{\text{ACC}} = PRF_K(x)$

with encrypted identity keys recoverable only by consensus authority:

$EID = TEnc_{n,d}([pk_i]_{i \in SC}, IDcredPUB)$

Allowing identifiability only with regulatory need, this scheme directly contrasts with pure privacy coins (Monero, Zcash) which preclude recovery.

A plausible implication is that threshold cryptographic approaches and attribute-based ZKPs offer flexible trade-offs between privacy and regulated identifiability, critical for KYC/AML compliance.

5. Identifiability in Hardware and Quantum Authentication Tokens

Identifiability is paramount for hardware IP protection (ICtoken (Balla et al., 9 Dec 2024)) and quantum authentication (ensemble-based quantum tokens (Tsunaki et al., 11 Dec 2024)):

• ICtokens hash unique physical IC identifiers and package marks:

$$\text{ICID} = \text{SHA256}(\text{Physical IC Identifier})$$

with blockchain-enforced immutability and multi-layer ownership provenance.

• Ensemble quantum tokens exploit measurement uncertainty and contrast to statistically discriminate genuine from forged tokens, with exponential suppression of false acceptance:

$p_f^M = (p_f)^M$

where $p_f$ is the forged single-token acceptance, and $M$ the number of ensemble tokens.

Physical binding, encryption, and cryptographic signing are implemented to guarantee unique, auditable, and nonduplicable token-to-object association. The state-of-the-art ensures that only authorized owners can claim or transfer hardware-embedded assets, and quantum protocols deliver probabilistic unforgeability below $10^{-22}$ for realistic ensemble sizes.

6. Identifiability in Decentralized Identity and Human-Unique Tokens

Human-centric identifiability is central in decentralized proof-of-unique-human protocols such as UniqueID (Hajialikhani et al., 2018). Each account is mapped via privacy-preserving biometrics (encrypted, obfuscated, or functionally encoded), verified by randomized social processes, and enforced on-chain such that one human can only ever own a single token. Cryptographic techniques (obfuscated biometric matching, ZKPs) underpin both privacy and unique binding:

$$\operatorname{PrivAI}(E_{pk}(B_i), E_{pk}(B_j)) := AI(B_i, B_j)$$

The registry enforces strict one-token-per-human policy. Sybil resistance is ensured by random assignment of human verifiers, entry barriers (stake/invitation), and adversarial audit mechanisms. Governance structures—trust delegation, democratic voting, punishment for misbehavior—are contingent on these identifiability guarantees.

A plausible implication is that large-scale social and economic systems (voting, UBI, reputation) are feasible only with robust technico-social identifiability mechanisms and continuous auditability.

7. Identifiability Challenges, Limitations, and Future Directions

Empirical results reveal continued challenges in practical identifiability: asset mutability, centralized metadata, impermanent storage, lack of uniqueness checks, and weak or fragmented ecosystem integration are endemic. Solutions explored include graph-based provenance, compositional audit chains, selective disclosure via threshold cryptography, zero-knowledge attribute proving, cryptographically enforced uniqueness, and hardware-rooted authentication.

The field continues to seek definitional and operational advances, including:

• New analytic frameworks for empirical uniqueness validation.
• Protocols for asset-permanence scoring and risk evaluation.
• Decentralized governance structures enforcing strong identifiability.
• Privacy-preserving techniques balancing auditability and fungibility.

A plausible implication is that future token infrastructures in distributed ledgers, digital identity, quantum authentication, and supply chain management will increasingly converge towards hybrid models: integrating compositional traceability, cryptographically controlled identifiability, and multi-party regulated accountability to support both privacy and trust.